<![CDATA[Soil fertility is an important factor that affects the growth and productivity of corn plants. Soil fertility assessments that are still carried out manually often produce different interpretations because they are influenced by the subjectivity of the observer. This study aims to design a soil fertility monitoring system using the Mamdani fuzzy logic method implemented through the MATLAB Fuzzy Logic Toolbox. The system uses three input parameters, namely soil pH, soil moisture, and soil temperature, with the output being the level of soil fertility. The data processing stages include fuzzification, application of IF–THEN-based rules, aggregation, and defuzzification using the centroid method to produce a definite output value. Simulation results show that the system is able to classify soil conditions into infertile, moderately fertile, and fertile categories consistently. The developed system can help users understand soil conditions more objectively and support decision-making in corn field management. Thus, the Mamdani fuzzy method is effective in processing uncertain environmental parameters into measurable information]]>
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